Yolov8 image object detection python | object detection google colab and YOLO | bounding box yolov8

Video Description

In this video, we will be doing image processing object detection using python and YOLOv8. This is a tutorial of google colab object detection from scratch using deep learning and computer vision library opencv. Object detection using machine learning and deep learning has been go to approach for image processing object detection. Yolo series has been the state of the art for quite some time now for single and multiple object detection. Yolov8 is the newest release for YOLO (You Only Look Once). The YOLO approach is the typical neural network object detection based approach which can give real time results. The YOLOv8 models come in different sizes and each can be used based on the task. We will be using Google colab for implementing the project and the code will be available on Github. The implementation obviously will be using Python. The project will also focus on getting the names of the predictions and the bounding boxes which could be used for further processing. We will also see how to interpret the bounding box outputs in yolo and infer the results from the yolo algorithm. We will see how to map class numbers to class labels from coco dataset. Code: https://github.com/DatumLearning/yolov8-image-object-detection Ultralytics Yolov8: https://github.com/ultralytics/ultralytics Yolov8 documentation: https://docs.ultralytics.com/